Sparse Linear Algebra
Scheduling Trees of Malleable Tasks for Sparse Linear Algebra
... within sparse direct solvers fit the model introduced by Prasanna and Musicus in [20] we conducted an experimental study on several dense linear algebra ...in sparse linear ...
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Fast and Accurate Simulation of Multithreaded Sparse Linear Algebra Solvers
... ∗ CNRS/Inria/University of Grenoble Alpes, France; firstname.lastname@imag.fr † Inria/University of Bordeaux, France; firstname.lastname@labri.fr ‡ CNRS/University Paul Sabatier, Toulouse, France; ...
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Evaluation of the OGF GridRPC Data Management library, and study of its integration into an International Sparse Linear Algebra Expert System
... for linear algebra aims at providing tools and softwares for sparse matrices (matrices with a higher ratio of zero components versus nonzero ...manipulate sparse linear algebra ...
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Scheduling Trees of Malleable Tasks for Sparse Linear Algebra
... its processing time is given by L i /p α i , where L i is the sequential duration of T i . The case α = 1 represents the unrealistic case of a perfect linear speed-up, and we rather concentrate on the case α < ...
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Use of A Network Enabled Server System for a Sparse Linear Algebra Grid Application
... This middleware is able to find an appropriate server according to the information given in the client’s request problem to be solved, size of the data involved, the performance of the t[r] ...
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Hierarchical hybrid sparse linear solver for multicore platforms
... Parallel sparse linear algebra solvers are often the innermost numerical kernels in scientific and engineering applications; consequently, they are one of the most time consuming ...large ...
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Efficient algorithms and implementation in exact linear algebra
... storing sparse matrix: mixing idea from sparse linear algebra community and introducing some specificity of exact ...of sparse matrix-vector product (SpMV for ...
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Towards an automatic generation of dense linear algebra solvers on parallel architectures
... dense linear algebra software is to propose a user-friendly Ap- plication Programming Interface (API) that can retain performance of BLAS-like [23] optimized ...dense linear algebra libraries ...
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Reordering Strategy for Blocking Optimization in Sparse Linear Solvers
... For future work, we plan to study the impact of our reordering strategy in a multi- frontal context with the Mumps [2] solver and compare it with the solution studied in [29], which performs the permutation during the ...
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2D Static Resource Allocation for Compressed Linear Algebra and Communication Constraints
... erations can be reduced from Θ(2/3n 3 ) to Θ(nk 2 log 2 n), where k is a parameter that represents the compression that can be achieved. Similar results have been proved in [6] for semi-separable matrices. Recently, ...
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Minimax rate of testing in sparse linear regression
... of linear regression model under sparse ...under sparse alternatives was first studied by Ingster (1997) and Donoho and Jin (2004) who considered the Gaussian mean ...to linear regression ...
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Bayesian Functional Linear Regression with Sparse Step Functions
... MSC 2010 subject classifications: Primary 62F15; secondary 62J05. Keywords: Bayesian regression, functional data, support estimate, parsimony. 1 Introduction Consider that one wants to explain the final outcome y of a ...
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Approximate cross validation for sparse generalized linear models
... Our main contribution is to demonstrate one case in which this notion of effective dimension is helpful for approximate CV - that of f, regularized generalized lin[r] ...
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Identification of switched linear systems via sparse optimization
... A first natural question is, under which conditions solv- ing the convex problem (16) can lead to the solution of the combinatorial problem (12). Second, can uniqueness be guaranteed for that solution. In order to ...
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Stacked Sparse Blind Source Separation for Non-Linear Mixtures
... a sparse linear BSS algorithm, provided that this one is robust to the higher amplitude non- ...found linear model, creating a new dataset R comprehending only the highest non-linear samples, ...
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SaaS for Energy Efficient Utilization of HPC Resources of Linear Algebra Calculations
... Several methods and techniques have been suggested and implemented to save energy at data centers and HPC resources. At the hardware level, the Dynamic voltage and frequency scaling (DVFS) method mainly is used, which ...
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SaaS for Energy Efficient Utilization of HPC Resources of Linear Algebra Calculations
... Several methods and techniques have been suggested and implemented to save energy at data centers and HPC resources. At the hardware level, the Dynamic voltage and frequency scaling (DVFS) method mainly is used, which ...
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Estimating linear functionals of a sparse family of Poisson means
... a linear functional of an unknown high- dimensional or even infinite-dimensional parameter were studied in the literature, mostly focusing on the case of a functional taking real values (as opposed to the vector ...
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Robust preconditioners via generalized eigenproblems for hybrid sparse linear solvers
... Maximum size of the local coarse space when imposing an a priori bound χ on the condition number. Note that AS and NN overlap with each other[r] ...
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Simulated Data for Linear Regression with Structured and Sparse Penalties
... for linear regression in which we control: The signal-to-noise ratio, the internal correlation structure of the data and the optimisation prob- lem that they are a solution ...
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